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A Cascading Fuzzy Logic Approach for Decision Making in Dynamic Applications

Mitchell, Sophia
http://orcid.org/0000-0003-3377-8487
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448037866

Abstract Details

2016, MS, University of Cincinnati, Engineering and Applied Science: Aerospace Engineering.
There is growing interest in the effectiveness of emulating human decision making and learning in modern aerospace applications. The following thesis is an examination of several applications in which cascading type 1 and 2 fuzzy logic has been utilized in artificial intelligence and machine learning problems to demonstrate its capabilities. In Fuzzy Logic Inferencing for PONG (FLIP), the effectiveness of cascading type 1 logic is examined as an optimal controller for players in the game of PONG. Robotic collaboration is also developed as the PONG game was expanded into a multi-player option. Precision Route Optimization using Fuzzy Intelligence (PROFIT) examines the use of fuzzy logic as an optimizer in a cascaded algorithmic solution to a modified Traveling Salesman Problem (TSP). The TSP is modified in a way to better mimic a real-life scenario where footprints must be visited instead of simply points, which gives an interesting complexity to the problem. Collaborative Learning using Fuzzy Inferencing (CLIFF) is an extension of the PONG game introduced in FLIP, however a type-2 fuzzy logic toolbox is developed for potential use in development of a robotic coach that could optimize its players to beat an opponent in an application of layered fuzzy learning. Considering the successes associated with these research endeavors, it can be concluded that cascading type 1 and 2 fuzzy logic are both interesting tools that can further the abilities of intelligent systems and machine learning algorithms.
Kelly Cohen, Ph.D. (Committee Chair)
Nicholas D. Ernest, Ph.D. (Committee Member)
Manish Kumar, Ph.D. (Committee Member)
Grant Schaffner, Ph.D. (Committee Member)
125 p.
Aerospace Materials
Fuzzy Logic; Cascading; Intelligent Systems; Artificial Intelligence; Travelling Salesman Problem; Genetic Algorithm

Recommended Citations

Citations

  • Mitchell, S. (2016). A Cascading Fuzzy Logic Approach for Decision Making in Dynamic Applications [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448037866

    APA Style (7th edition)

  • Mitchell, Sophia. A Cascading Fuzzy Logic Approach for Decision Making in Dynamic Applications. 2016. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448037866.

    MLA Style (8th edition)

  • Mitchell, Sophia. "A Cascading Fuzzy Logic Approach for Decision Making in Dynamic Applications." Master's thesis, University of Cincinnati, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448037866

    Chicago Manual of Style (17th edition)

ucin1448037866
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© 2016, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.
Release 3.2.12